Seed filling in domesticated maize and rice depends on SWEET-mediated hexose transport

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Abstract

Carbohydrate import into seeds directly determines seed size and must have been increased through domestication. However, evidence of the domestication of sugar translocation and the identities of seed-filling transporters have been elusive. Maize ZmSWEET4c, as opposed to its sucrose-transporting homologs, mediates transepithelial hexose transport across the basal endosperm transfer layer (BETL), the entry point of nutrients into the seed, and shows signatures indicative of selection during domestication. Mutants of both maize ZmSWEET4c and its rice ortholog OsSWEET4 are defective in seed filling, indicating that a lack of hexose transport at the BETL impairs further transfer of sugars imported from the maternal phloem. In both maize and rice, SWEET4 was likely recruited during domestication to enhance sugar import into the endosperm.

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A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase.

Paul Scheet, Matthew Stephens (2006)

We present a statistical model for patterns of genetic variation in samples of unrelated individuals from natural populations. This model is based on the idea that, over short regions, haplotypes in a population tend to cluster into groups of similar haplotypes. To capture the fact that, because of recombination, this clustering tends to be local in nature, our model allows cluster memberships to change continuously along the chromosome according to a hidden Markov model. This approach is flexible, allowing for both "block-like" patterns of linkage disequilibrium (LD) and gradual decline in LD with distance. The resulting model is also fast and, as a result, is practicable for large data sets (e.g., thousands of individuals typed at hundreds of thousands of markers). We illustrate the utility of the model by applying it to dense single-nucleotide-polymorphism genotype data for the tasks of imputing missing genotypes and estimating haplotypic phase. For imputing missing genotypes, methods based on this model are as accurate or more accurate than existing methods. For haplotype estimation, the point estimates are slightly less accurate than those from the best existing methods (e.g., for unrelated Centre d'Etude du Polymorphisme Humain individuals from the HapMap project, switch error was 0.055 for our method vs. 0.051 for PHASE) but require a small fraction of the computational cost. In addition, we demonstrate that the model accurately reflects uncertainty in its estimates, in that probabilities computed using the model are approximately well calibrated. The methods described in this article are implemented in a software package, fastPHASE, which is available from the Stephens Lab Web site.

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Sugar transporters for intercellular exchange and nutrition of pathogens.

Li-Qing Chen, Bi-Huei Hou, Sylvie Lalonde … (2010)

Sugar efflux transporters are essential for the maintenance of animal blood glucose levels, plant nectar production, and plant seed and pollen development. Despite broad biological importance, the identity of sugar efflux transporters has remained elusive. Using optical glucose sensors, we identified a new class of sugar transporters, named SWEETs, and show that at least six out of seventeen Arabidopsis, two out of over twenty rice and two out of seven homologues in Caenorhabditis elegans, and the single copy human protein, mediate glucose transport. Arabidopsis SWEET8 is essential for pollen viability, and the rice homologues SWEET11 and SWEET14 are specifically exploited by bacterial pathogens for virulence by means of direct binding of a bacterial effector to the SWEET promoter. Bacterial symbionts and fungal and bacterial pathogens induce the expression of different SWEET genes, indicating that the sugar efflux function of SWEET transporters is probably targeted by pathogens and symbionts for nutritional gain. The metazoan homologues may be involved in sugar efflux from intestinal, liver, epididymis and mammary cells.